| Validated risk prediction models for outcomes of acute kidney injury: a systematic review FN Haredasht, L Vanhoutte, C Vens, H Pottel, L Viaene, W De Corte BMC nephrology 24 (1), 133, 2023 | 12 | 2023 |
| Supervised fuzzy partitioning P Ashtari, FN Haredasht, H Beigy Pattern Recognition 97, 107013, 2020 | 12 | 2020 |
| Predicting outcomes of acute kidney injury in critically ill patients using machine learning F Nateghi Haredasht, L Viaene, H Pottel, W De Corte, C Vens Scientific Reports 13 (1), 9864, 2023 | 9 | 2023 |
| Comparison between cystatin C-and creatinine-based estimated glomerular filtration rate in the follow-up of patients recovering from a stage-3 AKI in ICU F Nateghi Haredasht, L Viaene, C Vens, N Callewaert, W De Corte, ... Journal of clinical medicine 11 (24), 7264, 2022 | 9 | 2022 |
| Red Teaming Large Language Models in Medicine: Real-World Insights on Model Behavior CTT Chang, H Farah, H Gui, SJ Rezaei, C Bou-Khalil, YJ Park, ... medRxiv, 2024.04. 05.24305411, 2024 | 6 | 2024 |
| Predicting survival outcomes in the presence of unlabeled data F Nateghi Haredasht, C Vens Machine Learning 111 (11), 4139-4157, 2022 | 5 | 2022 |
| The effect of different consensus definitions on diagnosing acute kidney injury events and their association with in-hospital mortality F Nateghi Haredasht, M Antonatou, E Cavalier, P Delanaye, H Pottel, ... Journal of Nephrology 35 (8), 2087-2095, 2022 | 5 | 2022 |
| Exploiting censored information in self-training for time-to-event prediction FN Haredasht, KA Dauda, C Vens IEEE Access, 2023 | 4 | 2023 |
| Causal inference of gene expression data using a clustering-based extension of kernel-granger causality FN Haredasht, F Ghassemi, MH Moradi 2016 23rd Iranian Conference on Biomedical Engineering and 2016 1st …, 2016 | 2 | 2016 |
| Clinical entity augmented retrieval for clinical information extraction I Lopez, A Swaminathan, K Vedula, S Narayanan, F Nateghi Haredasht, ... npj Digital Medicine 8 (1), 45, 2025 | 1 | 2025 |
| Comparison between the EKFC-equation and machine learning models to predict Glomerular Filtration Rate FK Nakano, A Åkesson, J de Boer, K Dedja, R D’hondt, FN Haredasht, ... Scientific reports 14 (1), 26383, 2024 | 1 | 2024 |
| Predictability of buprenorphine‐naloxone treatment retention: A multi‐site analysis combining electronic health records and machine learning F Nateghi Haredasht, S Fouladvand, S Tate, MM Chan, JJL Yeow, ... Addiction 119 (10), 1792-1802, 2024 | 1 | 2024 |
| Exploiting unlabeled data to predict the development of CKD after AKI in critically ill patients F Nateghi Haredasht, L Viaene, W De Corte, C Vens Intelligence Artificielle & Néphrologie 2021, Date: 2021/02/11-2021/02/12 …, 2021 | 1 | 2021 |
| Embedding-Driven Diversity Sampling to Improve Few-Shot Synthetic Data Generation I Lopez, FN Haredasht, K Caoili, JH Chen, A Chaudhari arXiv preprint arXiv:2501.11199, 2025 | | 2025 |
| Session Introduction: AI and Machine Learning in Clinical Medicine: Generative and Interactive Systems at the Human-Machine Interface FN Haredasht, D Kim, JD Romano, G Tison, R Daneshjou, JH Chen Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing 30, 33-39, 2025 | | 2025 |
| Quantization-free Lossy Image Compression Using Integer Matrix Factorization P Ashtari, P Behmandpoor, FN Haredasht, JH Chen, P Patrinos, ... arXiv preprint arXiv:2408.12691, 2024 | | 2024 |
| Improving 1-Year Mortality Prediction After Pediatric Heart Transplantation Using Hypothetical Donor-Recipient Matches M Venturini, FN Haredasht, F Sabovčik, RJH Miller, T Kuznetsova, C Vens Ieee Access, 2024 | | 2024 |
| Estimation of GFR with machine learning models compared to EKFC equation FK Nakano, A Lanot, A Akesson, H Pottel, P Delanaye, U Nyman, J Bjork, ... 2ème Conferénce Intelligence Artificielle Néphrologie, Date: 2023/09/14-2023 …, 2023 | | 2023 |
| Development of predictive models for critically ill patients with acute kidney injury F Nateghi Haredasht, C Vens, H Pottel, L Viaene, W De Corte | | 2023 |
| Serum Creatinine‑based versus Cystatin C‑based eGFR in AKI-stage3 critically ill patients F Nateghi Haredasht, L Viaene, C Vens, W De Corte, H Pottel ESICM–European society of intensive medicine, Date: 2022/05/12-2022/05/14 …, 2022 | | 2022 |
Celine Vensprofessor, Katholieke Universiteit Leuven在 kuleuven.be 的电子邮件经过验证
